Machine Learning for

Natural Language Processing

ENSAE, IP Paris

Natural Language Processing is a field of Artificial Intelligence concerned with processing human languages in a systematic way. It is now a mainstream technology used in a great variety of products like Voice Assistant, Search Engines, Recommander systems… This course is an exhaustive introduction to NLP. We will cover the full NLP processing pipeline, from preprocessing and representation learning to supervised task-specific learning.

Outline of the course

Lecture 1

The Basics of Natural Language Processing

Lecture 2

Representing text into vectors

Lecture 3

Deep Learning Methods for NLP

Lecture 4

Language Modeling

Lecture 5

Sequence Labelling & Sequence Classification of Text

Lecture 6

Sequence Generation for Text

Full Course Materials

Team

Instructor and Lecturer

Benjamin Muller, INRIA 🔗

Lab Main Instructor

Gaël Guibon, Télécom Paris 🔗

Lab Supervision

Ghazi Felhi, Université Paris 13 🔗
Roman Castagne
Matthieu Futeral-Peter

Evaluation

Students will be evaluated based on in-class quizzes and a final assignement project. The instructions of the final assignement can be found here 🔗

Logistics

The Lectures and Lab sessions will happen every Tuesday from February 1st to March 15th at ENSAE Paris between 9 am and 12.15 pm. Each session will be 3h (2x1h30).